Finance Fraud Detection

94% fewer false positives with autonomous fraud detection

FRACIFY deployed a swarm of 12 specialized AI agents to transform fraud operations for a digital bank processing 50M+ daily transactions across 12 countries.

Impact achieved

94%Fewer false positives

99.97%Fraud detection accuracy

$340MFraud prevented annually

About NexaPay

NexaPay is a leading digital banking platform operating across 12 countries, processing over 50 million transactions daily. The platform serves 24 million active users and handles $2.8B in transaction volume annually.

Employees

4,200

Annual Revenue

$1.8B

The challenge

Drowning in alerts, missing real threats

NexaPay's rule-based fraud detection system was generating an unmanageable volume of false positives — over 18% of legitimate transactions were flagged for manual review. A team of 200+ analysts was spending 80% of their time investigating false alarms while real fraud slipped through. The bank was losing $12M per quarter in abandoned transactions due to false declines, with actual fraud losses at $85M annually.

Top challenges

18% false positive rate overwhelming 200+ fraud analysts
Legacy ML models required weeks to retrain — too slow for evolving fraud patterns
$85M annual fraud losses with $12M quarterly revenue loss from false declines
No cross-channel fraud correlation across web, mobile, and API transactions

Skills deployed

Multi-agent AI fraud detection with 12 specialized agents
Real-time graph neural networks for synthetic identity detection
Explainable AI with full audit trails for regulatory compliance
Federated learning for cross-border fraud pattern recognition

The solution

Collaborative AI agents that think like fraud investigators

FRACIFY deployed a swarm of 12 specialized AI agents, each focused on a specific fraud vector. The agents operate in a collaborative architecture, sharing signals and building a unified risk profile for every transaction in under 12 milliseconds. Each agent specializes — transaction profiling, identity verification, network analysis, compliance monitoring — and they continuously learn from each other's findings.

FRACIFY OrchestratorGraph Neural NetworksTransformer Encoders Real-time Feature StoreApache KafkaFederated Learning Explainable AI Layer

Results

Tangible outcomes in the first quarter

Within the first quarter of full production deployment, FRACIFY's agent swarm transformed NexaPay's fraud operations:

94%Reduction in false positive rate — from 18% down to 1.1%

99.97%Detection accuracy for confirmed fraudulent transactions

$340MAnnual fraud prevention savings achieved

89%Reduction in manual review workload for analysts

"FRACIFY didn't just improve our metrics — it changed how we think about fraud. Our analysts now spend their time on high-value investigations and strategy instead of clicking through thousands of false alerts. The ROI in the first quarter alone exceeded our total investment."

— Sarah Chen

CTO, NexaPay

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